Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation

Emily Öhman; Kaisla Kajava; Jörg Tiedemann; Timo Honkela

doi:10.18653/v1/P17

Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation

Emily Öhman, Kaisla Kajava, Jörg Tiedemann, Timo Honkela

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Citations (Scopus)

Abstract

This paper introduces a gamified framework for fine-grained sentiment analysis and emotion detection. We present a flexible tool, Sentimentator, that can be used for efficient annotation based on crowd sourcing and a self-perpetuating gold standard. We also present a novel dataset with multi-dimensional annotations of emotions and sentiments in movie subtitles that enables research on sentiment preservation across languages and the creation of robust multilingual emotion detection tools. The tools and datasets are public and open-source and can easily be extended and applied for various purposes.

Original language	English
Title of host publication	WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop
Publisher	Association for Computational Linguistics (ACL)
Pages	24-30
Number of pages	7
ISBN (Electronic)	9781948087803
DOIs	https://doi.org/10.18653/v1/P17
Publication status	Published - 2018
Externally published	Yes
Event	9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2018 - Brussels, Belgium Duration: 2018 Oct 31 → …

Publication series

Name	WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop

Conference

Conference	9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2018
Country/Territory	Belgium
City	Brussels
Period	18/10/31 → …

ASJC Scopus subject areas

Language and Linguistics
Linguistics and Language

Access to Document

10.18653/v1/P17

Cite this

Öhman, E., Kajava, K., Tiedemann, J., & Honkela, T. (2018). Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation. In WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop (pp. 24-30). (WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/P17

Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation. / Öhman, Emily; Kajava, Kaisla; Tiedemann, Jörg et al.

WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop. Association for Computational Linguistics (ACL), 2018. p. 24-30 (WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Öhman, E, Kajava, K, Tiedemann, J & Honkela, T 2018, Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation. in WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop. WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop, Association for Computational Linguistics (ACL), pp. 24-30, 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2018, Brussels, Belgium, 18/10/31. https://doi.org/10.18653/v1/P17

Öhman E, Kajava K, Tiedemann J, Honkela T. Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation. In WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop. Association for Computational Linguistics (ACL). 2018. p. 24-30. (WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop). doi: 10.18653/v1/P17

Öhman, Emily ; Kajava, Kaisla ; Tiedemann, Jörg et al. / Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation. WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop. Association for Computational Linguistics (ACL), 2018. pp. 24-30 (WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop).

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AB - This paper introduces a gamified framework for fine-grained sentiment analysis and emotion detection. We present a flexible tool, Sentimentator, that can be used for efficient annotation based on crowd sourcing and a self-perpetuating gold standard. We also present a novel dataset with multi-dimensional annotations of emotions and sentiments in movie subtitles that enables research on sentiment preservation across languages and the creation of robust multilingual emotion detection tools. The tools and datasets are public and open-source and can easily be extended and applied for various purposes.

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Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation

Abstract

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